A case-control study of linear energy transfer and relative biological effectiveness related to symptomatic brainstem toxicity following pediatric proton therapy

Background and purpose A fixed relative biological effectiveness (RBE) of 1.1 (RBE1.1) is used clinically in proton therapy even though the RBE varies with properties such as dose level and linear energy transfer (LET). We therefore investigated if symptomatic brainstem toxicity in pediatric brain tumor patients treated with proton therapy could be associated with a variable LET and RBE. Materials and methods 36 patients treated with passive scattering proton therapy were selected for a case-control study from a cohort of 954 pediatric brain tumor patients. Nine children with symptomatic brainstem toxicity were each matched to three controls based on age, diagnosis, adjuvant therapy, and brainstem RBE1.1 dose characteristics. Differences across cases and controls related to the dose-averaged LET (LETd) and variable RBE-weighted dose from two RBE models were analyzed in the high-dose region. Results LETd metrics were marginally higher for cases vs. controls for the majority of dose levels and brainstem substructures. Considering areas with doses above 54 Gy(RBE1.1), we found a moderate trend of 13% higher median LETd in the brainstem for cases compared to controls (P =.08), while the difference in the median variable RBE-weighted dose for the same structure was only 2% (P =.6). Conclusion Trends towards higher LETd for cases compared to controls were noticeable across structures and LETd metrics for this patient cohort. While case-control differences were minor, an association with the observed symptomatic brainstem toxicity cannot be ruled out.publishedVersio

The Organ Sparing Potential of Different Biological Optimization Strategies in Proton Therapy

Purpose Variable relative biological effectiveness (RBE) models allow for differences in linear energy transfer (LET), physical dose, and tissue type to be accounted for when quantifying and optimizing the biological damage of protons. These models are complex and fraught with uncertainties, and therefore, simpler RBE optimization strategies have also been suggested. Our aim was to compare several biological optimization strategies for proton therapy by evaluating their performance in different clinical cases. Methods and Materials Two different optimization strategies were compared: full variable RBE optimization and differential RBE optimization, which involve applying fixed RBE for the planning target volume (PTV) and variable RBE in organs at risk (OARs). The optimization strategies were coupled to 2 variable RBE models and 1 LET-weighted dose model, with performance demonstrated on 3 different clinical cases: brain, head and neck, and prostate tumors. Results In cases with low in the tumor, the full RBE optimization strategies had a large effect, with up to 10% reduction in RBE-weighted dose to the PTV and OARs compared with the reference plan, whereas smaller variations (<5%) were obtained with differential optimization. For tumors with high the differential RBE optimization strategy showed a greater reduction in RBE-weighted dose to the OARs compared with the reference plan and the full RBE optimization strategy. Conclusions Differences between the optimization strategies varied across the studied cases, influenced by both biological and physical parameters. Whereas full RBE optimization showed greater OAR sparing, awareness of underdosage to the target must be carefully considered.publishedVersio

Influence of beam pruning techniques on LET and RBE in proton arc therapy

Introduction: Proton arc therapy (PAT) is an emerging treatment modality that holds promise to improve target volume coverage and reduce linear energy transfer (LET) in organs at risk. We aimed to investigate if pruning the highest energy layers in each beam direction could increase the LET in the target and reduce LET in tissue and organs at risk (OAR) surrounding the target volume, thus reducing the relative biological effectiveness (RBE)-weighted dose and sparing healthy tissue. Methods: PAT plans for a germinoma, an ependymoma and a rhabdomyosarcoma patient were created in the Eclipse treatment planning system with a prescribed dose of 54 Gy(RBE) using a constant RBE of 1.1 (RBE1.1). The PAT plans was pruned for high energy spots, creating several PAT plans with different amounts of pruning while maintaining tumor coverage, denoted PX-PAT plans, where X represents the amount of pruning. All plans were recalculated in the FLUKA Monte Carlo software, and the LET, physical dose, and variable RBE-weighted dose from the phenomenological Rørvik (ROR) model and an LET weighted dose (LWD) model were evaluated. Results and discussion: For the germinoma case, all plans but the P6-PAT reduced the mean RBE-weighted dose to the surrounding healthy tissue compared to the PAT plan. The LET was increasingly higher within the PTV for each pruning iteration, where the mean LET from the P6-PAT plan was 1.5 keV/μm higher than for the PAT plan, while the P4- and P5-PAT plans provided an increase of 0.4 and 0.7 keV/μm, respectively. The other plans increased the LET by a smaller margin compared to the PAT plan. Likewise, the LET values to the healthy tissue were reduced for each degree of pruning. Similar results were found for the ependymoma and the rhabdomyosarcoma case. We demonstrated a PAT pruning technique that can increase both LET and RBE in the target volume and at the same time decreased values in healthy tissue, without affecting the target volume dose coverage.publishedVersio

Combined RBE and OER optimization in proton therapy with FLUKA based on EF5-PET

Introduction Tumor hypoxia is associated with poor treatment outcome. Hypoxic regions are more radioresistant than well-oxygenated regions, as quantified by the oxygen enhancement ratio (OER). In optimization of proton therapy, including OER in addition to the relative biological effectiveness (RBE) could therefore be used to adapt to patient-specific radioresistance governed by intrinsic radiosensitivity and hypoxia. Methods A combined RBE and OER weighted dose (ROWD) calculation method was implemented in a FLUKA Monte Carlo (MC) based treatment planning tool. The method is based on the linear quadratic model, with α and β parameters as a function of the OER, and therefore a function of the linear energy transfer (LET) and partial oxygen pressure (pO2). Proton therapy plans for two head and neck cancer (HNC) patients were optimized with pO2 estimated from [18F]-EF5 positron emission tomography (PET) images. For the ROWD calculations, an RBE of 1.1 (RBE1.1,OER) and two variable RBE models, Rørvik (ROR) and McNamara (MCN), were used, alongside a reference plan without incorporation of OER (RBE1.1). Results For the HNC patients, treatment plans in line with the prescription dose and with acceptable target ROWD could be generated with the established tool. The physical dose was the main factor modulated in the ROWD. The impact of incorporating OER during optimization of HNC patients was demonstrated by the substantial difference found between ROWD and physical dose in the hypoxic tumor region. The largest physical dose differences between the ROWD optimized plans and the reference plan was 12.2 Gy. Conclusion The FLUKA MC based tool was able to optimize proton treatment plans taking the tumor pO2 distribution from hypoxia PET images into account. Independent of RBE-model, both elevated LET and physical dose were found in the hypoxic regions, which shows the potential to increase the tumor control compared to a conventional optimization approach.publishedVersio

The FLUKA Monte Carlo code coupled with an OER model for biologically weighted dose calculations in proton therapy of hypoxic tumors

Introduction: The increased radioresistance of hypoxic cells compared to well-oxygenated cells is quantified by the oxygen enhancement ratio (OER). In this study we created a FLUKA Monte Carlo based tool for inclusion of both OER and relative biological effectiveness (RBE) in biologically weighted dose (ROWD) calculations in proton therapy and applied this to explore the impact of hypoxia.Methods: The RBE-weighted dose was adapted for hypoxia by making RBE model parameters dependent on the OER, in addition to the linear energy transfer (LET). The OER depends on the partial oxygen pressure (pO(2)) and LET. To demonstrate model performance, calculations were done with spread-out Bragg peaks (SOBP) in water phantoms with pO(2) ranging from strongly hypoxic to normoxic (0.01-30 mmHg) and with a head and neck cancer proton plan optimized with an RBE of 1.1 and pO(2) estimated voxel-by-voxel using [F-18]-EF5 PET. An RBE of 1.1 and the Rorvik RBE model were used for the ROWD calculations.Results: The SOBP in water had decreasing ROWD with decreasing pO(2). In the plans accounting for oxygenation, the median target doses were approximately a factor 1.1 lower than the corresponding plans which did not consider the OER. Hypoxia adapted target ROWDs were considerably more heterogeneous than the RBE1.1-weighted doses.Conclusion: We realized a Monte Carlo based tool for calculating the ROWD. Read-in of patient pO(2) and estimation of ROWD with flexibility in choice of RBE model was achieved, giving a tool that may be useful in future clinical applications of hypoxia-guided particle therapy.</div

A hybrid multi-particle approach to range assessment-based treatment verification in particle therapy

Particle therapy (PT) used for cancer treatment can spare healthy tissue and reduce treatment toxicity. However, full exploitation of the dosimetric advantages of PT is not yet possible due to range uncertainties, warranting development of range-monitoring techniques. This study proposes a novel range-monitoring technique introducing the yet unexplored concept of simultaneous detection and imaging of fast neutrons and prompt-gamma rays produced in beam-tissue interactions. A quasimonolithic organic detector array is proposed, and its feasibility for detecting range shifts in the context of proton therapy is explored through Monte Carlo simulations of realistic patient models and detector resolution efects. The results indicate that range shifts of 1 mm can be detected at relatively low proton intensities (22.30(13) × 107 protons/spot) when spatial information obtained through imaging of both particle species are used simultaneously. This study lays the foundation for multiparticle detection and imaging systems in the context of range verifcation in PTpublishedVersio

A vér és a vérképzés gyógyszertana

Abstract Uncertainties in the proton range in tissue during proton therapy limit the precision in treatment delivery. These uncertainties result in expanded treatment margins, thereby increasing radiation dose to healthy tissue. Real-time range verification techniques aim to reduce these uncertainties in order to take full advantage of the finite range of the primary protons. In this paper, we propose a novel concept for real-time range verification based on detection of secondary neutrons produced in nuclear interactions during proton therapy. The proposed detector concept is simple; consisting of a hydrogen-rich converter material followed by two charged particle tracking detectors, mimicking a proton recoil telescopic arrangement. Neutrons incident on the converter material are converted into protons through elastic and inelastic (n,p) interactions. The protons are subsequently detected in the tracking detectors. The information on the direction and position of these protons is then utilized in a new reconstruction algorithm to estimate the depth distribution of neutron production by the proton beam, which in turn is correlated with the primary proton range. In this paper, we present the results of a Monte Carlo feasibility study and show that the proposed concept could be used for real-time range verification with millimetric precision in proton therapy

Hypoxia adapted relative biological effectiveness models for proton therapy: a simulation study

In proton therapy, a constant relative biological effectiveness (RBE) factor of 1.1 is applied although the RBE has been shown to depend on factors including the Linear Energy Transfer (LET). The biological effectiveness of radiotherapy has also been shown to depend on the level of oxygenation, quantified by the oxygen enhancement ratio (OER). To estimate the biological effectiveness across different levels of oxygenation the RBE-OER-weighted dose (ROWD) can be used. To investigate the consistency between different approaches to estimate ROWD, we implemented and compared OER models in a Monte Carlo (MC) simulation tool. Five OER models were explored: Wenzl and Wilkens 2011 (WEN), Tinganelli et al 2015 (TIN), Strigari et al 2018 (STR), Dahle et al 2020 (DAH) and Mein et al 2021 (MEI). OER calculations were combined with a proton RBE model and the microdosimetric kinetic model for ROWD calculations. ROWD and OER were studied for a water phantom scenario and a head and neck cancer case using hypoxia PET data for the OER calculation. The OER and ROWD estimates from the WEN, MEI and DAH showed good agreement while STR and TIN gave higher OER values and lower ROWD. The WEN, STR and DAH showed some degree of OER-LET dependency while this was negligible for the MEI and TIN models. The ROWD for all implemented models is reduced in hypoxic regions with an OER of 1.0–2.1 in the target volume. While some variations between the models were observed, all models display a large difference in the estimated dose from hypoxic and normoxic regions. This shows the potential to increase the dose or LET in hypoxic regions or reduce the dose to normoxic regions which again could lead to normal tissue sparing. With reliable hypoxia imaging, RBE-OER weighting could become a useful tool for proton therapy plan optimization.publishedVersio

Effect of an optimized X-ray blanket design on operator radiation dose in cardiac catheterization based on real-world angiography

Background There is increasing concern and focus in the interventional cardiology community on potential long term health issues related to radiation exposure and heavy wearable protection. Optimized shielding measures may reduce operator dose to levels where lighter radioprotective garments can safely be used, or even omitted. X-ray blankets (XRB) are commercially available but suffer from small size and lack of stability. A larger XRB may reduce operator dose but could hamper vascular access and visualization. The aim of this study is to assess shielding effect of an optimized XRB during cardiac catheterization and estimate the potential reduction in annual operator dose based on DICOM Radiation Dose Structured Report (RDSR) data reflecting everyday clinical practice. Methods Data accumulated from 7681 procedures over three years in our RDSR repository was used to identify projection angles and radiation doses during cardiac catheterization. Using an anthropomorphic phantom and a scatter radiation detector, radiation dose to the operator (mSv) and patient (dose area product—DAP) was measured for each angiographic projection for three different shielding setups. Relative operator dose (mSv/DAP) was calculated and multiplied by DAP per projection to estimate effect on operator dose. Results Adding an optimized XRB to a standard shielding setup comprising a table- and ceiling-mounted shield resulted in a 94.9% reduction in estimated operator dose. The largest shielding effect was observed in left and cranial projections where the ceiling-mounted shield offered less protection. Conclusions An optimized XRB is a simple shielding measure that has the potential to reduce operator dose.publishedVersio